Gene expression measurement using cDNA and oligo arrays continues to be a popular and useful technology for genomic analysis. High throughput methods for measuring protein concentrations are also increasing in popularity. One of the more challenging problems results from the large volume of data generated in these experiments. Image capture, processing, interpretation and quantification remain important fundamental issues. Quality control and experimental design must be carefully addressed. Many problematic statistical, image processing and bioinformatics issues remain and are addressed in this project.[unreadable] [unreadable] We have focused our research attention on developing new methods for analysis of gene splicing, based on microarray platforms especially designed for the purpose. We have developed and enhanced an analysis strategy using statistical ANOVA for efficient detection of potential splice events, and applied this technique to major publicly available data sets. We have also recently applied these approaches to studies of a mouse knock-out model, to a model of the inflammatory response of immune cells, and to the response of cells to an anti-cancer agent. Two measurement platforms, the Affymetrix exon array and the ExonHit junction probe array are being studied. Consideration is being given to the analysis of the entire Framiningham Heart Survey sample set using this new technology, which increases the available transcriptional information by roughly a factor of 10, compared to standard expression arrays.[unreadable] [unreadable] For many years, our group has functioned as the "statistical analysis core" for a high-volume microarray laboratory in CCMD/CC. All microarray studies by this group now pass through our analysis pipeline. We have now the analysis core for the microarray core facility for the NHLBI, more than tripling the throughput of microarray studies into our database and pipeline. Further, this "core" facility has generated more than a dozen new collaborative projects, in which our staff are primarily responsible for statistical treatment and interpretation of microarray data. In a major development this year, the NHLBI core and our Laboratory have accepted responsibility for data generation and analysis of the Framingham Heart Survey, comprising up to 7,000 biological samples. We will be augmenting our capabilities to handle this increase in workload.[unreadable] [unreadable] Affordable, high-quality software availability has been one of the bottlenecks in analysis of microarray data. We have continued development of the "MSCL Analyst's Toolbox" to address this need. Built upon the commercial statistical package JMP, this toolbox allows investigators to download Affymetrix microarray data from a central database, normalize and transform the data, inspect it for a variety of outliers or defects, perform a variety of statistical tests to select relevant genes affected in the experiment, and then visualize and classify various patterns of gene expression. Because our Toolbox is written in open source scripts, its statistical tests can be modified as needed to conform to novel or unique experimental designs. In collaboration with over forty investigators in CC, NHLBI, NIDCR and other ICs, this tool has been applied to several dozen microarray studies. One-day and two-day Toolbox training workshops are regularly presented on the NIH campus. [unreadable] [unreadable] In a major NIH-wide project, we maintain a database for storage, retrieval and analysis of Affymetrix microarrays, NIHLIMS. As part of this collaboration, we have created a data analysis pipeline and bioinformatics toolset, including both commercial and freely available software. The database currently stores information from over 2000 microarrays. Our downloadable tool set (MSCL Analyst's Toolbox) is now mature, widely tested and applied in numerous studies. Working with investigators in NCI, CC, NHLBI, NINDS, NIAID, NHGRI, NICHD, NIA, NIDDK, NIDA we have developed, customized and applied this software for the analysis of microarray based studies. We also maintain a quarterly-updated set of annotation files for use with Affymetrix data, in a format for convenient download and use by our collaborators.[unreadable] [unreadable] In a series of studies with investigators in NIDCR, we have analyzed gene expression in human monocytes before and after differentiation into dendritic cells, under stimulation by lipopolysaccharides derived from bacteria of interest to dental research. The goal is to reveal any basic differences in host response to different organisms, which may be useful diagnostically or therapeutically.[unreadable] [unreadable] In another study with investigators in NEI, we are evaluating the utility of several biological models for age-related macular degeneration and for retinal pigment epithelium (RPE) tissue development, using microarray technology. Preliminary results show that RPE tissues from several sources can be clearly distinguished from non-RPE, by the increased expression of a number of RPE-specific genes.[unreadable] [unreadable] In an ongoing proteomics initiatives, we collaborated with investigators in CCMD/CC in analysis of mass-spectroscopy (SELDI and MALDI) data to identify potential biomarkers of biological processes, diseases or syndromes. We have evaluated several technical modifications to the MALDI process which may allow for better discrimination of proteins by coupling MALDI with chromatographic separation.